Distance Perception in the Oculus Quest and Oculus Quest 2

Distances in virtual environments (VEs) viewed on a head-mounted display (HMD) are typically underperceived relative to the intended distance. This paper presents an experiment comparing perceived egocentric distance in a real environment with that in a matched VE presented in the Oculus Quest and Oculus Quest 2. Participants made verbal judgments and blind walking judgments to an object on the ground. Both the Quest and Quest 2 produced underperception compared to the real environment. Verbal judgments in the VE were 86\% and 79\% of real world judgments in the Quest and Quest 2, respectively. Blind walking judgments were 78% and 79% of real world judgments in the Quest and Quest 2, respectively. This project shows that significant underperception of distance persists even in modern HMDs.

Reality in a sphere: A direct comparison of social attention in the laboratory and the real world

Humans often show reduced social attention in real situations, a finding rarely replicated in controlled laboratory studies. Virtual reality is supposed to allow for ecologically valid and at the same time highly controlled experiments. This study aimed to provide initial insights into the reliability and validity of using spherical videos viewed via a head-mounted display (HMD) to assess social attention. We chose five public places in the city of Würzburg and measured eye movements of 44 participants for 30 s at each location twice: Once in a real environment with mobile eye-tracking glasses and once in a virtual environment playing a spherical video of the location in an HMD with an integrated eye tracker. As hypothesized, participants demonstrated reduced social attention with less exploration of passengers in the real environment as compared to the virtual one. This is in line with earlier studies showing social avoidance in interactive situations. Furthermore, we only observed consistent gaze proportions on passengers across locations in virtual environments. These findings highlight that the potential for social interactions and an adherence to social norms are essential modulators of viewing behavior in social situations and cannot be easily simulated in laboratory contexts. However, spherical videos might be helpful for supplementing the range of methods in social cognition research and other fields. Data and analysis scripts are available at https://osf.io/hktdu/.

INLA GOES TO SCHOOL AUGMENTED REALITY ANALYSIS AND DESIGN

lThis study describes the INLA Goes to School Gymnastics activities which have temporarily not been running for a year due to the pandemic. Therefore, this study makes analysis and design which will later be made into applications for further research so that INLA goes to school Gymnastics activities can be carried out again during a pandemic and after a pandemic. lAugmented Reality is a technology that allows users to see a combination of real and virtual objects in a real environment and run in real time or realtime. lIn this study, the author makes a 3-dimensional animation design to make it look more attractive and increase interest in using the INLA Goes to School Augmented Reality Gymnastics application. The INLA Goes to School Gymnastics Application Based on Augmented Reality was created using the Unity application and in the animation stage using the Blender application. Keywords: analysis; Android; application; augmented reality; INLA Abstrak: 1Penelitian ini mendeskripsikan tentang kegiatan Senam INLA Goes to School yang sementara belum berjalan selama setahun dikarenakan oleh pandemi. Maka dari itu penelitian ini membuat Analisa dan desain yang nantinya akan dibuatkan aplikasi dipenelitian selanjutnya agar kegiatan Senam INLA goes to school dapat dilakukan kembali disaat pandemic dan sesudah pandemi. Augmented Reality merupakan teknologi yang memungkinkan pengguna melihat gabungan benda nyata dan maya di lingkungan yang nyata dan berjalan pada waktu yang nyata atau realtime. 1lDalam penelitian ini, dapat membuat desain animasi 3 dimensi agar tampilan lebih menarik dan menambah minat dalam penggunaan aplikasi Augmented Reality Senam INLA Goes to School. 1Aplikasi Senam INLA Goes to School Berbasis Augmented Reality ini dibuat dengan menggunakan aplikasi Unity dan dalam tahap animasi menggunakan aplikasi Blender. Kata kunci: analisis; android; aplikasi; augmented reality; INLA

Intelligent Reading Recognition Method of Pointer Meter Based on Deep Learning in Real Environment

The accurate reading of pointer meter is a crucial task in complex environments such as substations, military and aerospace. The current recognition algorithm is mainly used to identify the same type and non-tilt meter, which has limited application in real environment. This paper proposes a novel end-to-end intelligent reading method of pointer meter based on deep learning, which locates the meter and extracts the pointer simultaneously without any prior information. Especially, the pointer is directly and precisely extracted using the designed semi-pointer detection method without any handcrafted features designed in advance, which avoids the accumulated error caused by preprocessing. Based on the extracted panel object, including semi-pointer, panel center and scale characters, the indicated value of the pointer is obtained by a local angle method, which can achieve better performance than the traditional angle method by referring to the neighboring scale lines of the pointer. Experimental results demonstrate that the method is faster and more effective than some common methods. It is worth noting that this study has the advantage of being able to recognize pointer meters in complex environments such as tilt, rotation, blur and illumination. It is acceptable for the actual application requirements in real environment with a recognition accuracy of 99.20% and the average reference error of 0.34%.

Four propellers submarine drone modelling in a real environment

<span lang="EN-US">In order to reduce the hydrodynamic dampers and mechanical elements as rudders, we have in our previous publications proposed our architectural solution of an ROV with only four thrusters without rudders or diving bars. In the results we have justified the choice of the arrangement of the thrusters. Also, we have started the kinematic and dynamic studies of the marine robot and we have especially demonstrated by using the mathematical model under MATLAB in the last publication, that this ROV can move in a perfect environment without gravity or hydrodynamic dampers. In this article, we will study the behavior of this marine vehicle in a real environment with gravity and hydrodynamic dampers and we will view if this architectural solution can really allow the ROV to move and execute the given directional instructions.</span>

Prefabricated Plug-and-Play Unitized Façade System for Deep Retrofitting: The RenoZEB Case Study

The retrofitting of the existing building stock is one of the most important goals to be pursued to meet European targets. In this context, the RenoZEB project has developed a modular methodology for the deep retrofitting of buildings, which is enabled by a prefabricated plug-and-play façade that integrates different on-market technologies to achieve nZEB standards. This article reports on the activities conducted in the study and design of the RenoZEB prefabricated envelope system, providing insights on the tests conducted and the results achieved for the façade system, with a specific focus on the use of technology laboratory facilities for real-environment validation, which revealed the system to be in line with the project objectives.

A Nuclide Recognition Method for Nuclear Robot System

In the real energy spectrum attenuation environment, many traditional nuclide identification methods for nuclear robot systems have problems such as using only part of the energy spectrum curve, being susceptible to noise, and having low recognition accuracy. Proposes an energy spectrum nuclide recognition method based on S-transform (ST) and Mahalanobis distance-based support vector machine (MSVM). Regarding the energy spectrum curve as a non-stationary signal, combined with the widely used S transformation method in signal transformation, the energy spectrum data is two-dimensional, Then use two-dimensional principal component analysis(2D-PCA) to reduce the dimension of the two-dimensional energy spectrum data for feature extraction, and design a support vector machine (SVM) classifier based on Mahalanobis distance to realize the identification of energy spectrum nuclides. Finally, experiments are carried out with simulated nuclide energy spectrum data based on Geant4. The experimental results show that this method effectively improves the accuracy of energy spectrum nuclide recognition by using full spectrum information. At the same time, experiments are carried out on the nuclide energy spectrum data of different detection distances obtained by the NaI detector in the real environment, and it is verified that the algorithm proposed in this paper also has a good recognition performance for the nuclide energy spectrum collected in the real environment.